Feature selection of an acoustic voice dataset for classification
It isn't obvious whether the 19 features are spectral and, if so, whether they contain detected transients for consonant phonics.  It's not obvious whether features were extracted using RBMs (restricted Boltzmann machines), from auto-correlation in the time domain, or some other way.  The intention of the classification, which would probably drive the nature of differentiation, isn't stated either.  If more details are added to the question, the answers may be more detailed.  Here are a few general options to compare.


Principal component analysis (PCA)
Factor analysis
Principal axis factoring
Cluster analysis
Regression or gradient descent if category labels exist and then checking early layer parameters for zeroes
Feature selection
Independent component analysis
Feature Selection: A Data Perspective, Jundong Li et. al. 2016